Currently, a facial recognition technology has been considered as a marketable recognition technology in the biometrics field due to the convenience in that there is no need to seek for a user's permission, which is different from a fingerprint recognition technology or an iris scan technology, and the applicability into various application fields. In particular, the facial recognition technology has been employed for a security system that authenticates an individual user or allows incoming and outgoing to thereby be used for incoming and outgoing management for each section and each time and recording of a travel path. The facial recognition technology has been applied as a security technology for preventing crimes and tracking down criminals. The facial recognition technology has been used to recognize a person who disguises the person's appearance by wearing a mask, sunglasses, and the like when the person accesses another user's account or directory to thereby illegally access a file or to attempt a financial criminal activity by forging the person's identity in a computer system.
Existing researches on detecting a disguised face with a mask or sunglasses determines the disguise depending on whether a facial detection succeeds or fails using a facial detection method about a normal face that is not disguised. Accordingly, even though the normal face is not properly detected, the normal face may be determined to be the disguised face. A face of a person who wears a mask or sunglasses does not have a normal facial feature and thus, it is very difficult to detect a disguised face by applying an existing facial detection and recognition method.
As an existing facial detection method, researches on detecting a facial outline or eyes and lips detecting a facial area using an oval template based on special edge information around a face or based on color information have been conducted. Proposed is a method capable of detecting a facial outline using a facial shape modeling based active shape model (ASM) matching scheme. As representative facial recognition methods, there are principle component analysis (PCA), elastic bunch graph matching, linear discriminant analysis (LDA), local feature analysis (LFA), and the like.
However, in the above methods, various facial shapes, a change in illumination, distortion of an input image, a change in posture, and the like may cause a facial area extraction error or may degrade the recognition performance. Therefore, there is a need for researches on a facial detection method and recognition method robust against the above-mentioned change factors.
Researches on a method of detecting and recognizing a disguised facial area have been conducted. However, in a disguised face, facial feature points such as eyes, a nose, lips, and the like are occluded by sunglasses or a mask and thus, it is difficult to detect a facial area with a facial detection method using a normal facial feature. Even though a method of detecting a face by modeling a facial shape is proposed, there was an obvious difference in the recognition performance or processing time based on an initial matching position of a facial model. In the case of the disguised face, due to a partially occluded facial area and a variety of disguised facial shapes, it is very difficult to recognize the disguised face, adaptable to an actual environment, using the proposed facial detection method and recognition algorithm.
Accordingly, there is a need for development of an algorithm that may accurately detect a facial area and determine whether a facial image is disguised using the detection result even though a portion of the facial area is occluded with sunglasses or a mask.